In data mining, a wrapper refers to a program that extracts content of a particular information source and translates it into relational form. A wrapper is typically hand-coded to be specific to a particular information source. This process can be tedious and error-prone. Wrapper induction refers to a technique in which wrappers may be automatically constructed. This automated technique aims to build algorithms that can learn wrappers on partially-, semi-, or un-structured documents from a set of labeled training data. Examples of such documents may include web pages, which are formatted for human browsing, rather than for use by a program. Providing labeled training data for every domain, although easier than building wrappers, is still a tedious and time-consuming task, given the large number of web domains.